292 results about "Observation method" patented technology

The invention discloses an adaptive genetic algorithm multi-satellite cooperative task dynamic scheduling planning method based on fusion and merging observation, and the method comprises the steps: firstly, decomposing regional tasks through equal-ratio sampling, and constructing discrete observation points; secondly, tasks are converted into a weighted meta-task set, and selectable satellites and time windows are calculated in combination with satellite resources, tasks and attitude constraints; further, detecting and combining the meta-tasks meeting conditions, and constructing a combined observation model taking the maximum observation benefit as a target; and finally, solving is optimized by adopting a self-adaptive genetic algorithm, constraint is ensured to be met, and an executable multi-satellite collaborative observation scheduling scheme is generated. In the regional task planning and scheduling process, a regional discrete adaptive sampling method is adopted to quickly decompose regional tasks into point tasks, and the completion rate of regional observation tasks is increased; in addition, an effective meta-task merging observation method is designed, and the multi-satellite dynamic task planning benefit is effectively improved.

The invention relates to the technical field of meteorological detection, in particular to a tornado collaborative observation method based on detection equipment. The method comprises the following steps: carrying out real-time monitoring on regional micro-pressure and meteorological echoes of a suspicious target region through a micromanometer and an S-band new-generation weather radar, and carrying out severe convection occurrence matching prediction to obtain a severe convection occurrence prediction target region; performing solar radio calibration processing on the corresponding radar detection equipment and triggering a tornado detection strategy cooperation instruction to perform severe convection target three-dimensional cooperation observation and target strong correlation area fusion division so as to generate a strong convection target and other strong correlation area radar field; performing equal-intensity convection characteristic analysis on the radar field of the equal-intensity correlation area of the severe convection target to generate a tornado equal-intensity convection characteristic data set; and obtaining a preset tornado feature library and carrying out tornado identification analysis to generate a tornado occurrence susceptible lattice point region. According to the invention, the monitoring precision and real-time performance of the tornado detection process can be improved.

The invention discloses an establishment method of a rock multi-field coupling model and the model thereof, and belongs to the technical field of engineering geological survey. Through comprehensive application of multi-scale modeling, a nondestructive testing technology, a machine learning algorithm and intelligent optimization, the problems that existing multi-physical field coupling analysis is not deep enough, the precision of an observation method is poor, and a device is prone to being damaged are solved, the advantages of various observations are combined, the building and analysis precision of a rock multi-field coupling model is improved, and the rock multi-field coupling analysis precision is improved. The method has the advantages that the method is simple and convenient to operate, the intelligence and automation level of the model is enhanced, microstructure data and macroscopic response are combined, deeper understanding of rock behaviors is provided, meanwhile, more accurate and efficient decision support can be provided for rock engineering design and construction, and the method is worthy of popularization and application. And a novel analysis and simulation method is provided for the field of rock mechanics research. Through the comprehensive scheme, behaviors of rocks under complex geological conditions can be better predicted and managed, so that the safety and economical efficiency of engineering are improved.

The invention discloses a service spacecraft multi-orbit maneuvering strategy approaching observation method based on J2 perturbation compensation, solves the problem of how to quickly improve orbit maneuvering accuracy, and belongs to the field of service spacecraft multi-orbit maneuvering strategy approaching observation. Comprising the following steps: constructing a motion equation under J2 item perturbation compensation under a target orbit coordinate system; constructing a service spacecraft multi-orbit maneuvering strategy model through the relative motion propagation relational expression and the motion equation; inputting the termination moment position conforming to the termination moment distance constraint into the model to output a single speed increment, and reserving the single speed increment conforming to the termination moment illumination angle constraint and the single speed increment constraint at the same time to obtain a speed increment solution set; constructing a circular region which takes the space target as a center and has a radius meeting a termination moment distance constraint; when the service spacecraft arrives at the circular area at a specified moment, marking the task successfully, and obtaining a service spacecraft multi-orbit maneuvering strategy for approaching observation; according to the invention, accurate and rapid track maneuvering is realized.

The invention relates to a dynamic environment settlement observation method, and relates to the technical field of data analysis, high-precision equipment is used for collecting settlement data and environment data in a settlement area, the timestamps, monitoring point numbers, temperature and humidity information of the data are recorded, and the settlement data and the environment data of the settlement area are preprocessed; the method comprises the steps of processing monitoring points, storing processed data in a database, extracting newly stored settlement data and environment data from the database, merging the settlement data and the environment data to form a new data set, calculating the settlement rate of each time period for each monitoring point, forming a settlement rate time sequence, performing trend analysis, and determining the settlement rate of each monitoring point. And constructing a settlement prediction model according to the settlement data and the analysis result, setting a dynamic settlement early warning threshold value based on the prediction result, when the monitoring data exceeds the early warning threshold value, triggering an alarm, checking whether the settlement height of each monitoring point exceeds the early warning threshold value, marking the monitoring point which triggers early warning as a settlement abnormal area, and generating a monitoring report.

The invention discloses a space-based directional observation method and device based on orbit precision evaluation. The method comprises the following steps: acquiring fixed star angular distance measurement data information, a Ka-band inter-satellite link observation value and an L-band satellite-ground link observation value of a Beidou satellite; using the information to construct a multi-dimensional observation matrix and carrying out resolving processing to obtain satellite position parameters corresponding to the three space-based directional observation modes; and performing comparison processing on the satellite position parameters by taking an MGEX precise ephemeris as a comparison baseline to obtain an optimal observation mode. Therefore, three space-based directional observation modes are provided, the orbit precision is used as an evaluation criterion, an observation mode system with high adaptability and high practicability is formed, and the orbit determination precision of the Beidou satellite is improved.

The invention provides a tunnel point position change automatic observation method and system combined with an AI algorithm, and relates to the technical field of tunnel monitoring, and the method comprises the steps: employing a speckle projector to form an irregular speckle pattern on a tunnel wall surface, and carrying out the multi-angle collection through a polarized light camera array, and obtaining the speckle intensity data; pre-embedding a coding microstructure generated based on quantum state superposition in the speckle pattern; establishing a speckle-stress correlation analysis model according to the speckle intensity data, and calculating three-dimensional displacement data in combination with the deformation data; and inputting the environmental monitoring data, the stress distribution data and the displacement data into the self-evolution heterogeneous feature network for analysis and prediction. According to the method, the measurement precision is improved by adopting the quantum coding speckles, the dynamic correlation analysis of multi-source data is realized through the self-evolution heterogeneous feature network, and the environmental adaptability and prediction accuracy of the system are enhanced.

The invention discloses a multi-satellite collaborative observation method and device, and the method comprises the steps: obtaining a training data set, task information and time window information; performing fusion processing on the training data set, the task information and the time window information to obtain to-be-processed collaborative observation information; and analyzing and calculating the task information, the time window information and the to-be-processed collaborative observation information to obtain target collaborative observation information. Therefore, according to the method, the decision speed of multi-satellite collaborative observation can be accelerated, so that the searching and optimizing difficulty and time consumption of satellite task planning are reduced.

The invention discloses a motor rotor state observation method and observer, and a motor rotor angle estimation system, and the observation method comprises the steps: obtaining a state parameter based on a current rotor state item and state parameter operation, and obtaining a voltage parameter based on a real-time sampling voltage and voltage parameter operation; integrating the current extension item, the state parameter item and the voltage parameter item to obtain an updated rotor state item, and updating the current rotor state item based on the updated rotor state item; and obtaining a current parameter item based on the real-time sampling current and the current parameter operation, integrating the current parameter item and the updated rotor state item to obtain an initial extension item, performing gain and amplitude limiting on the initial extension item based on the gain constant and the amplitude limiting parameter to obtain an updated extension item, and updating the current extension item based on the updated extension item. According to the invention, hardware acceleration in a rotor state acquisition process is realized, and the area of an electric control chip is reduced on the whole; and the dependence on high system frequency is also reduced, so that the operation power consumption of the system is reduced on the whole.

The present invention discloses a method for optimizing first data from an image set of an object observed in an observation apparatus by reconfiguring at least one parameter of the observation apparatus; the observation apparatus comprises an image sensor above a water surface; the image set of the object is captured by the image sensor. The method comprises: detecting, by a processing unit, a predetermined event based on second data, wherein the second data is associated with the image set of the object; and determining, by the processing unit, an execution of an instruction based on the predetermined event, wherein the instruction comprises a reconfiguration message which reconfigures the at least one parameter of the observation apparatus corresponding to the execution of the instruction.

The invention relates to the technical field of electric power facility safety monitoring, in particular to a substation equipment foundation settlement observation system and method, and the system comprises an infrared monitoring array and a data processing terminal; the method comprises the following steps: acquiring and correcting real-time three-dimensional point cloud data of the basic surface of the equipment; obtaining an effective settling volume; environment parameters or equipment vibration signals are monitored in real time, the collection frequency of the infrared monitoring array is automatically adjusted according to the monitoring result, and an early warning signal is sent out when the effective settling volume exceeds a preset threshold value; through software and hardware cooperation, the problems that in the prior art, a monitoring blind area is large, the anti-interference capacity is weak, and a linkage mechanism is lacked are solved, an intelligent settlement observation solution is provided for a substation equipment foundation, and safe and stable operation of a power grid is effectively guaranteed.

The invention relates to the technical field of water gauge observation, and discloses a water gauge intelligent observation method and system based on cooperation of multiple unmanned devices. The observation method comprises the following steps: acquiring ship far and near scene images and ship draft data; identifying water line data in the far and near scene images of the ship and water gauge symbol data corresponding to the water line data based on an improved YOLOV5 neural network; performing error optimization on the water line data and the water gauge symbol data by adopting a clustering algorithm to obtain initial water gauge observation data; dynamically allocating weights to the ship draft data and the preliminary water gauge observation data by adopting a Kalman filtering network, and performing weighted fusion on the ship draft data and the preliminary water gauge observation data to obtain fused water gauge observation data; the Kalman filtering network comprises a real-time state estimation network and a dynamic weight fusion network. The problems that a traditional manual water gauge is low in observation efficiency and high in risk, and an existing single-sensor water gauge is poor in anti-interference capacity, limited in severe environment observation and the like can be solved.

The invention discloses a severe convection refined collaborative observation method based on adjacent weather radar networking, and the method comprises the steps: selecting a weather radar station for networking as a networking member, and transmitting PPI data scanned by each group of networking members in real time to a data buffer for accumulation in a stream transmission communication mode; transmitting the data accumulated in the data buffer area to an algorithm server, processing and packaging the real-time PPI data on the algorithm server, and constructing a networking cooperation minute observation data set; observing the data set by networking collaboration minutes, developing networking products released by the service, and storing the generated products into a product data pool; and the downstream customer extracts the required product from the product data pool. According to the method, the application potential of multi-weather radar joint observation data in short-term and temporary services is fully excavated, the scanning updating frequency of a severe convection system is improved to 1 minute, and the observation grid horizontal density is encrypted to a sub-kilometer level.

The embodiment of the invention relates to the technical field of earth exploration, and discloses a magnetotelluric observation method, device and equipment in any observation direction and a medium, and the method comprises the steps: collecting electromagnetic field data of an electromagnetic field observation channel in magnetotelluric sounding in an observation area, and carrying out the data processing, and obtaining first electromagnetic field frequency spectrum data; the electromagnetic field observation channels comprise at least one electric field observation channel and two magnetic field observation channels, and the arrangement direction of each electric field observation channel and the arrangement direction of each magnetic field observation channel are non-orthogonal; vector transformation correction is carried out on the first electromagnetic field spectrum data to obtain second electromagnetic field spectrum data, and the second electromagnetic field spectrum data is orthogonal electromagnetic field data under an orthogonal coordinate system; and calculating an impedance tensor based on the second electromagnetic field spectrum data according to the number of the electric field observation channels. According to the method disclosed by the invention, the problem that traditional magnetotelluric observation is limited by complex terrain or observation conditions can be solved, and the application range of the magnetotelluric observation method is expanded.

The invention relates to the technical field of satellite navigation and ionosphere detection, in particular to a low-latitude ionosphere disturbance and non-uniform body multi-means collaborative detection and classification method. A multi-network cooperation-multi-source fusion observation mode is adopted, full space-time coverage of low-latitude ionosphere disturbance is achieved, in addition, a data fusion method based on physical constraints is applied, an ionosphere-middle atmosphere-troposphere multi-physics field coupling constraint mechanism is constructed, space-time consistency of data obtained through different observation means is optimized, and the low-latitude ionosphere disturbance is obtained. And finally, key characteristic parameters are extracted by using a multi-scale signal processing method, a disturbance characteristic matrix is constructed in combination with radar observation data (such as drift speed and spectral width), a'three-axis nine-element 'disturbance / non-uniform body classification standard is proposed firstly, then deep learning classification is used, accurate classification of low-latitude ionosphere disturbance is realized, and GNSS signal anomaly recognition capability is improved.

A sea wave time-frequency domain observation method based on binocular vision comprises the steps that a double-camera system is installed at two preset positions, and it is ensured that the double-camera system is aligned with the same sea surface area to synchronously observe sea waves; using a feature point matching technology to complete joint calibration of external parameters according to internal parameters of the camera; the image is filtered and corrected, noise is removed, and motion compensation is carried out according to needs; extracting three-dimensional point cloud data through a stereo matching algorithm, and constructing a three-dimensional form of sea waves; performing time-frequency domain analysis on the sea surface data, extracting sea wave parameters and performing time domain decomposition to comprehensively observe the dynamic characteristics of sea waves. The method overcomes the limitations of the traditional observation means, such as long laying time of the wave buoy, insufficient flexibility, high cost of the X-band wave radar, incapability of accurately obtaining the sea surface waveform and the like, provides technical support for ocean engineering and sea condition early warning, and has remarkable economic benefits and application prospects.

The application relates to the technical field of meteorological detection, in particular to a tornado cooperative observation method based on a detection device. The method comprises the following steps: performing real-time monitoring on regional micro-pressure and meteorological echoes of a suspicious target area through a micro-pressure gauge and an S-band new-generation weather radar, and performing strong convective occurrence matching prediction to obtain a strong convective occurrence prediction target area; performing solar radio calibration processing on corresponding radar detection equipment and triggering a tornado detection strategy cooperative instruction to perform strong convective target three-dimensional cooperative observation and target strong correlation area fusion division, so as to generate a strong convective target and strong correlation area radar field; performing strong convective feature analysis on the strong convective target and strong correlation area radar field, so as to generate a tornado and strong convective feature data set; acquiring a preset tornado feature library and performing tornado recognition analysis, so as to generate a tornado occurrence prone grid area. The application can improve the monitoring accuracy and real-time performance of the tornado detection process.

The invention discloses air tightness detection equipment for a hemodialysis pipeline, and belongs to the technical field of hemodialysis pipelines, the air tightness detection equipment for the hemodialysis pipeline comprises a glass box, a base fixed at the bottom of the glass box, a liquid outlet with a valve arranged at the central position of the bottom of the glass box, and a liquid supplementing pipe with a valve fixed on the side surface of the glass box, four supporting columns are installed at the bottom of the glass box, a glass inserting pipe is fixedly installed in the middle of the glass box, the two ends of the glass inserting pipe extend to the outer portion of the side face of the glass box and are in threaded connection with sealing plugs, and the rest part of the glass inserting pipe is located in the glass box. A plurality of through holes are formed in the side face, located in the glass box, of the glass inserting pipe, and an arc-shaped support is placed in the glass inserting pipe. The detection mode of the device does not damage the hemodialysis pipeline, the observation method is diversified, the operation is simple, the observation is convenient, the probability of negligence in the manual observation process is reduced, and the detection effect of the air tightness of the hemodialysis pipeline is improved.

The invention relates to a near space multi-target large-scale constellation collaborative observation method. All-weather tracking and detection are carried out on multiple targets flying at hypersonic velocity in near space based on a space-based observation system on-orbit satellite; comprising the following steps: S1, in the whole process of a near space multi-target large-scale constellation collaborative observation task, distributing and scheduling the near space multi-target large-scale constellation observation task by using a staged multi-source triggering collaborative observation task planning method; and S2, in a near space multi-target low-uncertainty stage, resource scheduling is carried out through a learning-based low-uncertainty multi-target collaborative observation task planning method. The method has the advantages that large-scale observation constellation resources are effectively distributed, the multi-target capacity is high, the target loss rate is low, and the resource utilization efficiency is high.

The invention discloses a secondary path online modeling and real-time ANC system observation method without additional white noise, and the method comprises the following steps: monitoring the stability of an ANC system through a real-time observer, and preventing divergence caused by the change of a secondary path or an overlarge step length; a secondary path online modeling method is designed, secondary path online precise modeling without adding white noise is realized by combining an offline modeling initial value and online self-adaptive updating, and residual noise rise and human ear discomfort caused by introduction of the white noise in a traditional online modeling method are avoided; secondary path coupling is eliminated by using a loudspeaker time-sharing sounding strategy, and the modeling calculation amount is reduced; and an intelligent ANC system is constructed, a secondary path model is dynamically updated, the step length is adaptively adjusted, and stable operation of the system is ensured. According to the invention, the stability and the noise reduction performance of the ANC system are improved, and the calculation complexity and the human ear interference risk are reduced at the same time.

The application discloses a kind of based on GNSS's dam vertical displacement monitoring reference network automation observation method.It includes the following steps, step one: point site reconnaissance, instrument and observation pier selection;Step two: GNSS data preprocessing and scheme optimization;In GNSS vertical displacement automation monitoring, determine the optimal observation period, repair frequent small cycle jump;Step three: baseline solution and network adjustment method;In GNSS vertical displacement automation monitoring, troposphere delay correction, thermal expansion effect correction these models are applied to baseline solution, introduce prior height difference information in network adjustment, improve the accuracy and reliability of baseline solution.The application has the advantages of improving the vertical direction of GNSS baseline solution precision.The application also discloses a kind of based on GNSS's dam vertical displacement monitoring reference network automation observation platform.

The invention belongs to the technical field of power transmission channel meteorological monitoring, and particularly relates to a power transmission channel strong convection strong wind observation method and system. Determining an observation mode adopted for strong convection gale observation according to the environmental condition parameters; determining a strong convection gale observation result of the target power transmission channel based on the selected observation mode; the observation mode comprises laser or microwave. According to the technical scheme provided by the invention, the advantages of high sensitivity of the laser wind measurement technology and strong penetration, weak attenuation and the like of the microwave wind measurement technology are fused, the laser radar and the microwave radar are systematically integrated, and the current external environment is automatically judged, so that laser / microwave is adaptively switched to serve as a main channel for strong convection strong wind observation; the observation efficiency and the observation accuracy are improved, and then accurate observation of strong convection strong wind of the power transmission channel is achieved.

The invention discloses a spatial distributed observation method based on irregular region geometric feature sampling, and belongs to the technical field of aerospace. The implementation method comprises the following steps: establishing a coordinate system for describing the motion of the spacecraft; establishing a spacecraft dynamic model under the coordinate system; six initial orbit elements of a satellite can be obtained based on existing low-orbit constellation orbit data, the spatial position is calculated through the orbit elements, and then position components are converted into latitude and longitude coordinates, namely sub-satellite point coordinates; defining vertex coordinates of the polygon, and constructing a planar polygon by connecting the vertex coordinates end to end; discretizing the internal region of the closed polygon; on the basis of the kinetic model, on the basis of the coordinates of the sub-satellite point and the center coordinates of the discrete sampling circle, calculating the characteristic distance from the sampling point in the observation area to the sub-satellite point, and on the basis of the size relationship between the characteristic distance and the radius of the observation view field, judging whether the irregular area can be successfully observed in a preset time constraint interval; therefore, spatial distributed observation is realized.

According to the intelligent observation method, device and equipment for the weather phenomenon and the storage medium provided by the invention, the collected multi-source data is intelligently identified and analyzed through machine learning models such as the cloud condition identification model, the rainfall identification model and the thunder and lightning identification model, and key meteorological elements such as cloud height, cloud category, rainfall intensity, rainfall type and thunder and lightning activity are automatically generated; manual intervention is reduced, and observation precision and automation level are improved. Moreover, a plurality of sensing devices, such as an image acquisition device, a weather radar, a rainfall sensor, a recording device and the like, are introduced to obtain multi-dimensional weather information and cover a plurality of weather phenomena such as cloud conditions, rainfall, thunder and lightning and the like, so that the problem of single data source of a traditional meteorological observation means is overcome, and the comprehensiveness and reliability of observation are enhanced.

The invention provides a space debris bistatic detection data fusion method based on a Bayesian rule, and the method comprises the following steps: 1, building a detection model: obtaining a detection probability and detection data distribution through a space-based in-situ simulation detection model and a foundation narrow-beam radar simulation detection model based on the orbit parameters of given space debris; step 2, inputting detection data and performing inversion; and step 3, calculating the number of fragments by using a space debris bistatic detection data fusion method based on a Bayesian rule. According to the method, the limitation of a single observation mode is overcome, and the reliability of environment modeling is improved; compared with a single data source, the data obtained by the two detection modes can complement each other, and the obtained information is more complete; and theoretical support is provided for cooperation of fragment monitoring. Data fusion supports data sharing of space monitoring institutions of different countries and regions to cope with challenges brought by space debris together.

The invention discloses a buoy type wave observation method and device based on a GNSS and an accelerometer, and relates to the technical field of marine environment monitoring, and the method comprises the steps: collecting positioning data and inertial motion data, constructing a reference acceleration through the positioning data, carrying out the dynamic real-time zero offset compensation of the acceleration, correcting the attitude of a buoy according to the angular velocity information, and carrying out the real-time zero offset compensation of the acceleration. Wave motion parameters are calculated by using a multi-order spectral moment, a horizontal velocity component is extracted, the main wave direction of waves is estimated through a maximum entropy spectrum method, and the main wave direction and the wave motion parameters are jointly packaged and transmitted through a dual-mode communication link. Through multi-source synchronous acquisition, GNSS dynamic zero offset compensation, attitude correction, wave direction calculation and parameter inversion, the problem of low accuracy and reliability of observation data caused by long-term drifting of the wave observation buoy is cooperatively solved, and meanwhile, the maintenance difficulty and cost of the wave buoy are reduced. A core algorithm is realized through an edge processing architecture, so that the cost of a single buoy is greatly reduced, and possibility is provided for large-scale high-density networking.

The application discloses a car with a friction gap of safety clamps convenient to observe, which comprises a car body and a bracket frame arranged at the end of the car body, the bracket frame is movably matched with a guide rail, a safety clamp assembly is connected to the outer side of the bracket frame, a friction gap is left between the guide rail and the safety clamp assembly, the friction gap is a brake distance reserved between the safety clamp assembly and the guide rail, and the car further comprises an observation part, the line of sight of a human eye can pass through the observation part to observe the state of the friction gap in the inner side area of the bracket frame. The car with the friction gap of safety clamps convenient to observe can avoid the limitation of the guide rail on the observation angle during the observation process, can make the observation angle directly face the friction gap, and thus the observation precision and the observation efficiency are improved.

To provide a novel technique of observing change of a water surface different from a wave.SOLUTION: The observation program causes a computer to execute processing of: acquiring data of a radar image formed by periodically observing a sea area as an observation target by a radar device using electric waves of 0.01 m-2 m lengths; calculating an average image formed by averaging the radar image shown by the acquired data at every specific average time in order of the observation times; and outputting information based on the calculated average image.SELECTED DRAWING: Figure 6

The present invention relates to the technical field of geographic information systems, and discloses a sensor observation method and system based on Cesium. In this observation method, a viewing frustum is constructed using the PerspectiveFrustum function, and the parameters of different types of sensors are customized to adjust the observation perspective, and the target to be observed within the viewing frustum is observed, thereby simulating the sensor observation environment. The present invention solves the problems existing in the prior art, such as not supporting the customization of different types of sensors to adjust the current perspective and being difficult to observe various targets in a complex environment from multiple angles in real time.